Recognising visual patterns to communicate gas turbine time-series data

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)


We have observed that visual patterns play an important part when domain experts interpret time series data. Such patterns change their appearance when displayed at different time scales and a systematic method is proposed to handle this problem. First, a rapid change detector combined with a dynamic limit checker (DRCD) is employed to detect primitive patterns at a basic time scale. Patterns obtained at that time scale are then transformed into patterns viewed at a higher time scale and the DRCD algorithm is reused at this time scale to identify new visual patterns that did not appear at lower time scales. An evaluation of the preliminary results is promising.

Original languageEnglish
Title of host publicationApplications and Innovations in Intelligent Systems X
Subtitle of host publicationProceedings of ES2002, the Twenty-Second SGAI International Conference on Knowledge Based Systems and Applied Artificial Intelligence
EditorsAnn L. Macintosh, Richard Ellis, Frans Coenen
Place of PublicationLondon, UK
Number of pages14
ISBN (Print)9781852336738, 1852336730
Publication statusPublished - 2003

Publication series

NameBCS Conference Series


Dive into the research topics of 'Recognising visual patterns to communicate gas turbine time-series data'. Together they form a unique fingerprint.

Cite this